Data Driven Chat: “The potential of data is not realized in most organizations”
Ganna Pogrebna in conversation with Briana Brownell — Underrated skills in data science, getting executive buy-in, and how we can all shape the future
Academic, Educator, Consultant, and Blogger Ganna Pogrebna started Data Driven Chat to explore the many interesting aspects of behavioural data science including human behaviour, data science and AI. Ganna Pogrebna is Professor of Behavioral Analytics and Data Science and a Lead of Behavioral Data Science strand at the Alan Turing Institute — the national centre for AI and Data Science in London (UK). The Data Driven Chat is the official podcast of the Behavioral Data Science Special Interest Group at Turing.
Data scientist turned tech entrepreneur Briana Brownell is the founder and CEO of Pure Strategy Inc. Using the leading edge technology in natural language processing, machine learning and neural networks Pure Strategy’s Automated Neural Intelligence Engine (ANIE) gives organizations the insights needed to make decisions confidently.
The conversation originally appeared on Data Driven Chat. Click here to listen.
This is Part 2 of a three-part series. You can read Part 1 and Part 3 here.
Ganna: We’ll come back to the topic of Covid-19 a bit later but first, I want to ask you — a lot of people who listen to this podcast are aspiring data scientists and trying to find a place in data science. Can you give some tips to people who want to get into this kind of liaison between decision science and data science? Where do they start? What do they need to do?
Briana: I think that the underappreciated skill in data science is communication and business acumen. Having the technical skills to run the models and be able to do those technical things like programming in Python and understanding databases are really important but the truth is, when you’re working in industry, it’s all about how that analysis can impact the metrics that the business cares about. So if you are not able to link what you’re doing to a goal that the business has or an outcome that’s really important, it’s really really hard to get resources and it’s difficult to be effective if you’re doing something that is not a high priority within the business.
“I think that the underappreciated skill in data science is communication and business acumen.”
This is where I see data scientists really struggling. In an organization, when you do modelling with data that isn’t linked to any kind of outcome, these teams often get pushed to the side or they get minimized within the organization. It’s so sad because data science can be so impactful.
Technical skills extremely important but being able to communicate the value of that to the business is even more important.
Ganna: Yeah certainly — and you mentioned that what is also important is the problem statements, right? How do you support answering important questions for business? That’s another thing that everybody needs to be able to do as an aspiring data scientist. How do we approach data in the business context? Why do you think understanding data is particularly important for businesses now? Do you think the potential of data is still not realized?
Briana: Great questions. I do think that the potential of data is not realized in most organizations and there are several reasons for this. The first one is siloed data within organizations. I’ve worked with organizations where they had multiple teams that were essentially collecting the same information but because of political reasons within the organization, they were unwilling to share that data back and forth across departments. I think that’s really dangerous because that’s a sign of a poorly functioning organization. If there’s no way to share data across different groups in the organization, that’s always a challenge.
Second, individuals often don’t know what’s possible with data, especially when you get to the c-suite and the executive level. All of these techniques are so new it’s difficult to know exactly what the payoff might be in doing a larger scale analysis project within the organization. Sometimes the project essentially is a failure and sometimes you can get additional insight but you don’t necessarily know until you try. That’s sometimes a real barrier when executives want to see certain ROI on their data programs.
Ganna: And how did data change the business landscape in the last few years or did it change? Do you observe the change?
Briana: I think that the biggest change in how data is used in organizations is that, say 10 years ago, it was rare to have a data project make it all the way up to the c-suite or the board level. The executives would never actually see any results of a data analytics project. They would be within the marketing group, they might be within the IT group or they might be within the sales group. They were kept within those small silos and they would never make it up to the executive level in the organization.
But after people started seeing the value of it, we started seeing buy-in at the highest levels of the organization. Not only were executives asking for better data, better analytics, better modelling, but boards of directors were asking for it. You saw a board mandate saying “We need to have some kind of data-driven metric for each quarter. We need to see this metric.”
“All of this information went to the highest levels of the organization and that, I think, was a really new thing.”
All of this information went to the highest levels of the organization and that, I think, was a really new thing. Before, a lot of financial metrics were always reported to the board and the executive but now the marketing metrics, the operations research metrics, all of these areas are finding themselves in the boardroom and I think that that’s a really positive sign.
Ganna: But also at the same time, I want to challenge what you said. I feel that there is at the same time a lack of understanding in the board about data science that it is not a magic wand that you solve the problems with.
If you don’t have high quality data, there’s not much you could do. Maybe the insights are not as valuable. I feel that there is often lack of understanding of methodology. People would look at insignificant results or look at too few data points to be able to make a decision.
It’s critical to have people like you who come in and explain that that’s probably not a good idea, you need to look here instead to have a proper decision intelligence and decisions insight using data. So do you feel that on the one hand, it is great that there is data, but it’s just too much hype about what data can do?
Briana: You’re absolutely right. I think that it’s interesting because a lot of the times I’ve seen there’s been one or two people on the board or the executive team that really understand data well. If you have that person as the champion for the analytics projects that you’re doing it really helps.
“There’s a lot of interest for organizations to train people as citizen data scientists. You can be in any role in the organization and you augment your skills with a better understanding of data and how it pertains to your role.”
There are absolutely cases where people misunderstand the data. The data is not clean, for example, or it has some kind of a bias in it and that’s always a challenge because you can make decisions on data that isn’t necessarily as strong as you think it is.
Where I see that changing is that there’s a lot of interest for organizations to train people as citizen data scientists. You can be in any role in the organization and you augment your skills with a better understanding of data and how it pertains to your role. I see that more and more where large organizations are providing training, getting consultants to lead work groups around how data is used and how it’s understood within the organization. So I’m hopeful that the challenges that you mentioned — which are absolutely true challenges — are starting to get better and better. I’m hoping within 10 years we’re going to be out of the woods on that.
Ganna: Yeah I also hope so. Like you mentioned, it’s cool when you have a person who can translate sophisticated data insights for the board. We recently were working with big corporate client and we had a person who had a PhD in physics and this guy is amazing! I mean, he can turn any piece of sophisticated analysis into bar charts, mappings and graphs and all that. He turned all of it into like very, very simple bar charts. It was awesome! I was thinking, wow! You can actually do all of this just in such a simple way.
I want to ask you several questions about women in stem. Because you were CEO yourself and you’re in a very high tech, I male-dominated environment, in your opinion do we have a lack of female CEOs? And if so why do we have this problem? What do you think are the underlying reasons for that?
Briana: I do wish that there were more women CEOs leading deep tech and in high tech companies because first of all, I just think it’s a fascinating area. I think it’s so important and it allows people to be shapers of the future instead of just being impacted by the technology that comes along.
As far as why I think there are fewer women that are doing these kinds of things — one of the most important things is visibility, for women and young girls to see that it’s a viable career path for them. There are so many women that I know who just happened to become lawyers or veterinarians or other similar professions and the only reason that they didn’t go into tech isn’t that they weren’t good at it or anything, it was just because they didn’t know that they could. They just didn’t know anyone who was an engineer or a computer scientist or who worked in that area and they didn’t realize it was an option for them.
By seeing people who are doing interesting things and being exposed to it is extremely important, and being able to see people who are like them in some of these roles.
“There are so many women that I know who just happened to become lawyers or veterinarians or other similar professions and the only reason that they didn’t go into tech is they didn’t realize it was an option for them.”
I’ll never forget Gwynne Shotwell, who’s such an amazing person and engineer, and COO of SpaceX. One of the things that she said was the reason that she became an engineer was that a female engineer had come to speak at her school and she was wearing a really amazing suit. At first, that sounds really silly like, “Oh whoa! Why is it so important what she was wearing?” But what it reveals is that this girl wanted to see herself in that role, in that profession. It wasn’t the suit, it was “does this allow me to see myself in this role? Can I see myself as an engineer? What would it be like if I were an engineer? Or a data scientist or technologist?” And I think that that’s extremely important.
Ganna: I like how you talk about role models. You talk about these role models as in you don’t necessarily need a specific person; you can have someone who comes in a cool suit and that kind of inspires. ‘Actually I want that!’ right? I want to be in space, I want to work with this group of people, just like this woman, yes? And that example is cool.
I want to zoom out a little bit on this diversity, inclusivity, and to talk about more than modern women because even if we just take the females, if we look at Fortune 500 — and we just recently did this with one of my students and some of my colleagues — we actually found out that if we look at women’s representation in the Fortune 500 is not great, right? But if we look at, for example, minorities then the situation is just really bad. For example if we look for women of colour, there are just three of them leading Fortune 500 companies and none of them are black. So it seems like the system is broken somewhere. What can we do to increase inclusivity in tech industries?
Briana: I think that it’s about creating an environment where people feel that they belong. I had mentioned that people need to be able to see themselves in those roles, so being able to see someone like you in a senior role and realize that that’s a possible career path for you, I think that that’s really important. When you don’t see anyone like you it’s easy to feel that you don’t belong, right?
Everyone, every human has a need to belong and be a part of a group that has that sense of community around it. And so being able to create those groups is so important. I’m seeing more and more online support groups or groups where people can gather and share their experiences, share their stories, share advice. I think that that’s a really positive sign to be able to create these groups where you feel like you can be yourself, that you belong there, that people aren’t going to judge you or think that you’re strange for having the interest that you do. This is a really important part of a much bigger and really challenging picture.
Ganna: As many of my students are executive students, they are constantly worried about technical skills that they need. You mentioned that you came from a technical background and you are CEO and but in terms of the technical skills that you need to lead in the current conditions, do you think that it’s important to know how to code? Is it important to understand how algorithms work? What level of technical ability do you need as a leader today? Not only as a female leader, but in general, what skills are important for leadership today?
Briana: If you’re leading a technology company it’s much easier to find excellent talent if, at the top levels of the organization, you have someone with great technical skills. The reason for that is, a lot of technical folks, when they first start out in their career, almost all of us have the experience of working for a non-technical leader who didn’t understand really what we were doing, marginalized it, had unrealistic expectations — who was basically very difficult to work for. And so when you’re a technical person, you want to work for someone who understands some of those issues and someone who will advocate for you as a contributor to an important part of the company and not marginalize development and the technical prowess that it takes to make a company succeed.
“If you’re leading a technology company it’s much easier to find excellent talent if, at the top levels of the organization, you have someone with great technical skills.”
So it’s not critical for the CEO, for example, to be a programmer or to know how to code, but you either need to have a good enough understanding of how software architecture works that you can respect the opinions and the knowledge level that’s within your technical team or you need to partner with someone who does have that knowledge and who can advocate for the technical team in a way that’s respectful to their skill set.
I find that one of the challenges that women leaders often face is that they’ll be a non-technical CEO or non-technical founder who are invariably looking for a technical co-founder right? And that relationship can absolutely work as long as the co-founder who is leading the technical side has enough respect from the original founder to be able to create something that works for the business. Instead of being just ‘Oh I have this idea! Can you just code it for me?’ Because that just never works. It just doesn’t work to bring someone on to just to code something. The respect for the technical skills and the technical needs of the company needs to be in there.
Ganna: Yeah, talking about it and about horrible bosses, I just remembered I once worked for a person who asked me to regress the variable on itself to get the perfect correlation! I was like, ‘Are you sure about this?!’ I mean, the lack of understanding is a big problem.
I completely hear when you’re saying that attracting talent would be a lot easier if you also had the reputation.
Coming back to your point about role models, if people know that you have reputation in the tech industry you can definitely attract people that would be good.
Briana: Yes, absolutely.
This is Part 2 of a three-part series. Click here to listen to the whole conversation.
Part 1: Data Driven Chat: “It was something that really mattered.”
Ganna Pogrebna in conversation with Briana Brownell — The chapters of her data science journey, impactful projects and current work in health care.
Part 3: Data Driven Chat: “We didn’t do a very good job of building resiliency into really important industries.”
Ganna Pogrebna in conversation with Briana Brownell — What COVID-19 showed us about data science, how life after COVID-19 will be different, resilient systems and recommended reading and watching on AI.
